An answered call for aid? Cannabinoid clinical framework for the opioid epidemic.

BACKGROUND: The opioid crisis continues in full force, as physicians and caregivers are desperate for resources to help patients with opioid use and chronic pain disorders find safer and more accessible non-opioid tools. MAIN BODY: The purpose of this article is to review the current state of the opioid epidemic; the shifting picture of cannabinoids; and the research, policy, and current events that make opioid risk reduction an urgent public health challenge. The provided table contains an evidence-based clinical framework for the utilization of cannabinoids to treat patients with chronic pain who are dependent on opioids, seeking alternatives to opioids, and tapering opioids. CONCLUSION: Based on a comprehensive review of the literature and epidemiological evidence to date, cannabinoids stand to be one of the most interesting, safe, and accessible tools available to attenuate the devastation resulting from the misuse and abuse of opioid narcotics. Considering the urgency of the opioid epidemic and broadening of cannabinoid accessibility amidst absent prescribing guidelines, the authors recommend use of this clinical framework in the contexts of both clinical research continuity and patient care.

Comparing empirical kinship derived heritability for imaging genetics traits in the UK biobank and human connectome project.

Imaging genetics analyses use neuroimaging traits as intermediate phenotypes to infer the degree of genetic contribution to brain structure and function in health and/or illness. Coefficients of relatedness (CR) summarize the degree of genetic similarity among subjects and are used to estimate the heritability - the proportion of phenotypic variance explained by genetic factors. The CR can be inferred directly from genome-wide genotype data to explain the degree of shared variation in common genetic polymorphisms (SNP-heritability) among related or unrelated subjects. We developed a central processing and graphics processing unit (CPU and GPU) accelerated Fast and Powerful Heritability Inference (FPHI) approach that linearizes likelihood calculations to overcome the ∼N2-3 computational effort dependency on sample size of classical likelihood approaches. We calculated for 60 regional and 1.3 × 105 voxel-wise traits in N = 1,206 twin and sibling participants from the Human Connectome Project (HCP) (550 M/656 F, age = 28.8 ± 3.7 years) and N = 37,432 (17,531 M/19,901 F; age = 63.7 ± 7.5 years) participants from the UK Biobank (UKBB). The FPHI estimates were in excellent agreement with heritability values calculated using Genome-wide Complex Trait Analysis software (r = 0.96 and 0.98 in HCP and UKBB sample) while significantly reducing computational (102-4 times). The regional and voxel-wise traits heritability estimates for the HCP and UKBB were likewise in excellent agreement (r = 0.63-0.76, p < 10-10). In summary, the hardware-accelerated FPHI made it practical to calculate heritability values for voxel-wise neuroimaging traits, even in very large samples such as the UKBB. The patterns of additive genetic variance in neuroimaging traits measured in a large sample of related and unrelated individuals showed excellent agreement regardless of the estimation method. The code and instruction to execute these analyses are available at www.solar-eclipse-genetics.org.

Homogenizing Estimates of Heritability Among SOLAR-Eclipse, OpenMx, APACE, and FPHI Software Packages in Neuroimaging Data.

Imaging genetic analyses use heritability calculations to measure the fraction of phenotypic variance attributable to additive genetic factors. We tested the agreement between heritability estimates provided by four methods that are used for heritability estimates in neuroimaging traits. SOLAR-Eclipse and OpenMx use iterative maximum likelihood estimation (MLE) methods. Accelerated Permutation inference for ACE (APACE) and fast permutation heritability inference (FPHI), employ fast, non-iterative approximation-based methods. We performed this evaluation in a simulated twin-sibling pedigree and phenotypes and in diffusion tensor imaging (DTI) data from three twin-sibling cohorts, the human connectome project (HCP), netherlands twin register (NTR) and BrainSCALE projects provided as a part of the enhancing neuro imaging genetics analysis (ENIGMA) consortium. We observed that heritability estimate may differ depending on the underlying method and dataset. The heritability estimates from the two MLE approaches provided excellent agreement in both simulated and imaging data. The heritability estimates for two approximation approaches showed reduced heritability estimates in datasets with deviations from data normality. We propose a data homogenization approach (implemented in solar-eclipse; www.solar-eclipse-genetics.org) to improve the convergence of heritability estimates across different methods. The homogenization steps include consistent regression of any nuisance covariates and enforcing normality on the trait data using inverse Gaussian transformation. Under these conditions, the heritability estimates for simulated and DTI phenotypes produced converging heritability estimates regardless of the method. Thus, using these simple suggestions may help new heritability studies to provide outcomes that are comparable regardless of software package.

Genomic kinship construction to enhance genetic analyses in the human connectome project data.

Imaging genetic analyses quantify genetic control over quantitative measurements of brain structure and function using coefficients of relationship (CR) that code the degree of shared genetics between subjects. CR can be inferred through self-reported relatedness or calculated empirically using genome-wide SNP scans. We hypothesized that empirical CR provides a more accurate assessment of shared genetics than self-reported relatedness. We tested this in 1,046 participants of the Human Connectome Project (HCP) (480 M/566 F) recruited from the Missouri twin registry. We calculated the heritability for 17 quantitative traits drawn from four categories (brain diffusion and structure, cognition, and body physiology) documented by the HCP. We compared the heritability and genetic correlation estimates calculated using self-reported and empirical CR methods Kinship-based INference for GWAS (KING) and weighted allelic correlation (WAC). The polygenetic nature of traits was assessed by calculating the empirical CR from chromosomal SNP sets. The heritability estimates based on whole-genome empirical CR were higher but remained significantly correlated (r ∼0.9) with those obtained using self-reported values. Population stratification in the HCP sample has likely influenced the empirical CR calculations and biased heritability estimates. Heritability values calculated using empirical CR for chromosomal SNP sets were significantly correlated with the chromosomal length (r 0.7) suggesting a polygenic nature for these traits. The chromosomal heritability patterns were correlated among traits from the same knowledge domains; among traits with significant genetic correlations; and among traits sharing biological processes, without being genetically related. The pedigree structures generated in our analyses are available online as a web-based calculator (www.solar-eclipse-genetics.org/HCP).

Fast and powerful genome wide association of dense genetic data with high dimensional imaging phenotypes.

Genome wide association (GWA) analysis of brain imaging phenotypes can advance our understanding of the genetic basis of normal and disorder-related variation in the brain. GWA approaches typically use linear mixed effect models to account for non-independence amongst subjects due to factors, such as family relatedness and population structure. The use of these models with high-dimensional imaging phenotypes presents enormous challenges in terms of computational intensity and the need to account multiple testing in both the imaging and genetic domain. Here we present a method that makes mixed models practical with high-dimensional traits by a combination of a transformation applied to the data and model, and the use of a non-iterative variance component estimator. With such speed enhancements permutation tests are feasible, which allows inference on powerful spatial tests like the cluster size statistic.

Expression- and genomic-level changes during passage of four baculoviruses derived from bacmids in permissive insect cell lines.

The baculovirus-based bacmid expression vector system has been widely used for protein production in basic research and biotechnological laboratories. Since the first construction of the Autographa californica multiple nucleopolyhedrovirus bacmid (AcBacmid), three more bacmids have been created from Bombyx mori nucleopolyhedrovirus (BmBacmid), Spodoptera exigua nucleopolyhedrovirus (SeBacmid) and Helicoverpa armigera nucleopolyhedrovirus (HaBacmid). Each of these bacmid-derived viruses replicates efficiently in a range of specific and permissive cell types. Here, we investigated the relative stability of each virus derived from the bacmid during passage in permissive cell lines through assessment of their expression level and genome structure changes. Using two different reporters, the expression levels of the viruses from the AcBacmid-Sf9, AcBacmid-Tn5, BmBacmid-BmN and SeBacmid-SeE1 bacmid-cell systems were significantly reduced after five passages of the viruses, whereas the reductions were not detected in the AcBacmid-Sf21 and HaBacmid-HzAM1 systems. Pulse field gel electrophoresis (PFGE) and restriction fragment length polymorphism (RFLP) analysis of viral DNA isolated from passaged viruses from the AcBacmid-Sf21 and HaBacmid-HzAM1 systems showed no major genomic changes. In contrast, the genomes from passaged viruses in the AcBacmid-Tn5 and AcBacmid-Sf9 systems displayed reduced genome size and various mutations at individual loci, including genotypes missing one at least or more viral RNA polymerase subunits and fp25k. These genotypic changes were correlated with reduced protein expression. RFLP analysis of viral DNA from passaged viruses in the BmBacmid-BmN and SeBacmid-SeE1 systems exhibited changes in genome size, including excision of particular EcoRI fragments containing the mini-F replicon. Collectively, our data suggest that the viruses from the AcBacmid-Sf21 and HaBacmid-HzAM1 bacmid-cell systems are better for large-scale protein expression in continuous culture. Further study is needed to investigate the mechanism(s) behind the protein expression reduction in these bacmid-derived virus/cell systems.

Infectious disease.

Athletes are susceptible to the same infections as the general population. However, special considerations often need to be taken into account when dealing with an athlete who has contracted an infectious disease. Health care providers need to consider how even common illnesses can affect an athlete's performance, the communicability of the illness to team members, and precautions/contraindications related to athletic participation. Recent advances in the prevention, diagnosis, and/or management of frequently encountered illnesses, as well as certain conditions that warrant special attention in the athletic setting, are discussed in detail.

Understanding the issues of intellectual property in the creation of e-learning courseware.

This article provides an introduction to copyright law and guidance on constructing the collaborative agreements between faculty and staff coworkers, and faculty and institutional administration to encourage the development of e-learning courseware and its use in an extended distance environment.

Efficacy of a rapamycin analog (CCI-779) and IFN-gamma in tuberous sclerosis mouse models.

Tuberous sclerosis complex (TSC) is a familial tumor disorder for which there is no effective medical therapy. Disease-causing mutations in the TSC1 or TSC2 gene lead to increased mammalian target of rapamycin (mTOR) kinase activity in the conserved mTOR signaling pathway, which regulates nutrient uptake, cell growth, and protein translation. The normal function of TSC1 and TSC2 gene products is to form a complex that reduces mTOR kinase activity. Thus, mTOR kinase inhibition may be a useful targeted therapeutic approach. Elevated interferon-gamma (IFN-gamma) expression is associated with decreased severity of kidney tumors in TSC patients and mouse models; therefore, IFN-gamma also has therapeutic potential. We studied cohorts of Tsc2+/- mice and a novel mouse model of Tsc2-null tumors in order to evaluate the efficacy of targeted therapy for TSC. We found that treatment with either an mTOR kinase inhibitor (CCI-779, a rapamycin analog) or with IFN-gamma reduced the severity of TSC-related disease without significant toxicity. These results constitute definitive preclinical data that justify proceeding with clinical trials using these agents in selected patients with TSC and related disorders.